194
Views
0
CrossRef citations to date
0
Altmetric
Articles

Estimation of coronary stenosis severity based on flow distribution ratios

ORCID Icon, &
Pages 424-438 | Received 30 Jun 2020, Accepted 14 Jul 2021, Published online: 28 Jul 2021
 

Abstract

We suggest improving minimally-invasive stenosis severity estimation, using a combination of existing geometry-based methods with Transluminal Attenuation Gradient measurements. Instead of local flow values, the method uses flow distribution ratios along the entire tree. The tree geometry is used to derive a lumped model and predict the ‘theoretical’ ratios in each bifurcation, while attenuation measurements are used for extracting ‘actual’ ratios. The discrepancies between the measured and the theoretical values are utilized to assess a functional degree of stenosis. Our experimental and numerical analyses show that the quantitative value of discrepancy is proportional to stenosis severity, regardless of boundary conditions.

Acknowledgements

We would like to thank Mr. Eliya Shimol for his support with the numerical model and Mr. Ben Avrahami for his help with the algorithm for the lumped model.

Disclosure statement

The authors have no relevant conflicts of interest to disclose.

Additional information

Funding

Hadar Biran was supported by a scholarship provided by Ariel University. The research was partially supported by a grant from the Nicholas and Elizabeth Slezak Super Center for Cardiac Research and Biomedical Engineering at Tel Aviv University.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.